The Use of Machine Learning for Inferencing the Effectiveness of a Rehabilitation Program for Orthopedic and Neurological Patients

Valter Santilli, Massimiliano Mangone, Anxhelo Diko, Federica Alviti, Andrea Bernetti, Francesco Agostini (), Laura Palagi, Marila Servidio, Marco Paoloni, Michela Goffredo, Francesco Infarinato, Sanaz Pournajaf, Marco Franceschini, Massimo Fini and Carlo Damiani
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Valter Santilli: Department of Anatomy, Histology, Forensic Medicine and Orthopedics, Sapienza University, Piazzale Aldo Moro 5, 00185 Rome, Italy
Massimiliano Mangone: Department of Anatomy, Histology, Forensic Medicine and Orthopedics, Sapienza University, Piazzale Aldo Moro 5, 00185 Rome, Italy
Anxhelo Diko: Department of Anatomy, Histology, Forensic Medicine and Orthopedics, Sapienza University, Piazzale Aldo Moro 5, 00185 Rome, Italy
Federica Alviti: Department of Anatomy, Histology, Forensic Medicine and Orthopedics, Sapienza University, Piazzale Aldo Moro 5, 00185 Rome, Italy
Andrea Bernetti: Department of Anatomy, Histology, Forensic Medicine and Orthopedics, Sapienza University, Piazzale Aldo Moro 5, 00185 Rome, Italy
Francesco Agostini: Department of Anatomy, Histology, Forensic Medicine and Orthopedics, Sapienza University, Piazzale Aldo Moro 5, 00185 Rome, Italy
Laura Palagi: Department of Computer, Control and Management Engineering Antonio Ruberti, Sapienza University, Piazzale Aldo Moro 5, 00185 Rome, Italy
Marila Servidio: Department of Anatomy, Histology, Forensic Medicine and Orthopedics, Sapienza University, Piazzale Aldo Moro 5, 00185 Rome, Italy
Marco Paoloni: Department of Anatomy, Histology, Forensic Medicine and Orthopedics, Sapienza University, Piazzale Aldo Moro 5, 00185 Rome, Italy
Michela Goffredo: Department of Neurological and Rehabilitation Science, IRCCS San Raffaele Roma, Via della Pisana 235, 00163 Rome, Italy
Francesco Infarinato: Department of Neurological and Rehabilitation Science, IRCCS San Raffaele Roma, Via della Pisana 235, 00163 Rome, Italy
Sanaz Pournajaf: Department of Neurological and Rehabilitation Science, IRCCS San Raffaele Roma, Via della Pisana 235, 00163 Rome, Italy
Marco Franceschini: Department of Neurological and Rehabilitation Science, IRCCS San Raffaele Roma, Via della Pisana 235, 00163 Rome, Italy
Massimo Fini: Department of Neurological and Rehabilitation Science, IRCCS San Raffaele Roma, Via della Pisana 235, 00163 Rome, Italy
Carlo Damiani: Department of Neurological and Rehabilitation Science, IRCCS San Raffaele Roma, Via della Pisana 235, 00163 Rome, Italy

IJERPH, 2023, vol. 20, issue 8, 1-16

Abstract: Advance assessment of the potential functional improvement of patients undergoing a rehabilitation program is crucial in developing precision medicine tools and patient-oriented rehabilitation programs, as well as in better allocating resources in hospitals. In this work, we propose a novel approach to this problem using machine learning algorithms focused on assessing the modified Barthel index (mBI) as an indicator of functional ability. We build four tree-based ensemble machine learning models and train them on a private training cohort of orthopedic (OP) and neurological (NP) hospital discharges. Moreover, we evaluate the models using a validation set for each category of patients using root mean squared error (RMSE) as an absolute error indicator between the predicted mBI and the actual values. The best results obtained from the study are an RMSE of 6.58 for OP patients and 8.66 for NP patients, which shows the potential of artificial intelligence in predicting the functional improvement of patients undergoing rehabilitation.

Keywords: artificial intelligence; machine learning; rehabilitation; Barthel Index; algorithms; functional improvement (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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